滚动轴承的智能诊断系统研究

Research on Intelligent Fault Diagnosis System of Rolling Bearings

利用虚拟仪器平台,选用加速度传感器和声级计拾取滚动轴承的振动信号和声信号,运用小波分析提取轴承特征信号;构建了基于BP神经网络的数据融合结构,实现轴承故障的智能诊断,提高了诊断效率和准确性.

The acceleration sensor and the sound level meter are selected to collect vibration signals and the sound signals of the rolling bearings by using the virtual instrument platform. Then the feature signals are extracted by using the wavelet analysis. Data fusion structure is established based on the BP neural network, which realizes intelligent fault diagnosis of rolling bearings and enhances the diagnosis efficiency and accuracy.